Basiri, A;
Jackson, M;
Amirian, P;
Pourabdollah, A;
Sester, M;
Winstanley, A;
Moore, T;
(2016)
Quality assessment of OpenStreetMap data using trajectory mining.
Geo-Spatial Information Science
, 19
(1)
pp. 56-68.
10.1080/10095020.2016.1151213.
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Abstract
OpenStreetMap (OSM) data are widely used but their reliability is still variable. Many contributors to OSM have not been trained in geography or surveying and consequently their contributions, including geometry and attribute data inserts, deletions, and updates, can be inaccurate, incomplete, inconsistent, or vague. There are some mechanisms and applications dedicated to discovering bugs and errors in OSM data. Such systems can remove errors through user-checks and applying predefined rules but they need an extra control process to check the real-world validity of suspected errors and bugs. This paper focuses on finding bugs and errors based on patterns and rules extracted from the tracking data of users. The underlying idea is that certain characteristics of user trajectories are directly linked to the type of feature. Using such rules, some sets of potential bugs and errors can be identified and stored for further investigations.
| Type: | Article |
|---|---|
| Title: | Quality assessment of OpenStreetMap data using trajectory mining |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/10095020.2016.1151213 |
| Publisher version: | https://doi.org/10.1080/10095020.2016.1151213 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Spatial data quality, OpenStreetMap (OSM), trajectory data mining |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10058579 |
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